Methodology
How passive telemetry measures Focus, Momentum and Friction
How FlowStatus turns Figma activity metadata into three signals design leaders can act on: what each one captures, why it matters, and where its limits are.
- Updated:
- 26 September 2026
- By:
- MoreThought, makers of FlowStatus
- Reading time:
- 8 minutes
Summary
| Signal | Question it answers | What it looks at | Healthy looks like |
|---|---|---|---|
| Focus | Can people sustain attention on the problem? | Movement between files; session patterns | Sustained, shared attention on a small set of files |
| Momentum | Is the work moving consistently? | How regularly the project is worked on | Steady activity; no long dormant spells |
| Friction | Where does work stall, loop or wait? | Rounds of work, pauses and convergence | Short, regular rounds that converge |
What passive telemetry is, and isn't
Passive telemetry is behavioural data emitted automatically by the tools teams already use. For design organisations, the richest source is the Figma organisation activity log: a time-stamped record of who opened, created, renamed, moved, exported or shared which file.
Because it is generated as a by-product of work, it has three properties that surveys, workshops and time sheets lack. It is continuous (no reporting cadence), complete (every team, not a sample of volunteers) and unobtrusive (no one is asked to do anything differently).
| Used | Not used |
|---|---|
| Actor (email or ID) | Design files, frames, layers or canvas contents |
| Timestamp of each action | Prototypes or exported assets |
| Action type, e.g. view, create, rename, move, export | Comment bodies and chat text |
| File key and name | Keystrokes, screen recording or time tracking |
| Project, team and division names | Figma passwords or write access |
For how to get this data out of Figma, by CSV export or the Activity Logs API, see the Figma activity audit guide.
From events to signals
Every metric passes through the same six stages.
- 1
Collect
Events arrive through the Figma Activity Logs API (read-only OAuth scope
org:activity_log_read) or an activity-log CSV exported from Figma Admin. - 2
Normalise
Event names from the API and CSV exports are mapped to a common set of actions, timestamps are aligned to a single time zone and duplicates are removed.
- 3
Attribute
Each file is attributed to its Figma project and team, and optionally to a division, so every signal can be read at project, team, division and organisation level.
- 4
Sessionise
Each designer's actions on a project are grouped into working sessions, so the analysis sees blocks of effort rather than isolated clicks.
- 5
Score
Focus, Momentum and iteration patterns are computed per project, then rolled up to teams and portfolios in a way that stops one large project masking many struggling small ones.
- 6
Trend
Scores are recomputed over rolling windows, so leaders see whether conditions are improving after a reorganisation, hiring wave or process change.
Focus: is attention sustained or fragmented?
Focus is a proxy for the cognitive conditions under which good design work happens: sustained, undivided attention on a problem. Research on attention residue shows that when people switch tasks, part of their attention stays with the task they left. In Figma, that switching leaves a clean behavioural trace: consecutive actions on different files.
File-switching
The simplest view of focus is switch rate: how often a designer's next action is on a different file. A designer who works in one file before moving on switches rarely; a designer hopping between ten files in an afternoon switches constantly. In the Design Telemetry Benchmark, projects with very low switching averaged 3.1/5 on outcomes against 2.1/5 for high switching.
The FlowStatus Focus score
The product goes further than switching alone. It looks at how each designer's work on a project breaks into sessions: how many there are, how long they last, how concentrated they are in time, and how much they overlap with other people's work and other projects. Fewer, longer, concentrated sessions indicate higher focus.
Supporting views show how many sessions work typically needs and how much of each person's time goes to their main project, which highlights people carrying fragmented portfolios.
Momentum: is the work moving consistently?
Momentum measures consistency: how much of a project's life actually has work happening in it. Stop-start projects lose context each time they restart; steady projects compound it.
A project worked on most days scores highly. One that is touched sporadically, with long pauses between bursts, scores low even if the bursts themselves are intense. Momentum is deliberately independent of team size: a small team working steadily outscores a large team working in fits and starts.
Momentum also tracks dormancy: extended periods with no activity at all. A project with a dormant spell is effectively two projects sharing a name, and both the gap and its cause are worth investigating. Very small projects are not scored, so one-off visits are not mistaken for healthy work.
Friction: where does work stall, loop or wait?
Friction is the resistance a project meets on the way to an outcome. It is not directly observable as a single event, so FlowStatus infers it from the shape of activity over time. In the product, friction surfaces mainly through Iteration health and the bottleneck views.
Work rounds and convergence
Activity on a project naturally clusters into work rounds: bursts of iteration separated by pauses. Two properties of those rounds reveal friction: how long the pauses are, and whether each round is smaller than the last (the work is converging) or as big as ever (it is still expanding).
Iteration patterns
Each project is assigned one pattern, with convergence reported alongside it.
| Pattern | What it looks like | What it usually means |
|---|---|---|
| Fast | Several short, regular rounds that converge | Clear brief and aligned stakeholders |
| Quick | One or two tight rounds, then shipped | Small, well-defined piece of work |
| Moderate | A handful of rounds | Normal iterative progress |
| Stalled | Little iteration, long pauses between rounds | Blocked, waiting on decisions, or deprioritised |
| Thrashing | Many rounds, erratic pauses, not converging | Rework without convergence; unstable scope |
The friction signal families
| Friction type | What you see | Typical cause |
|---|---|---|
| Stall | Long pauses between few rounds of work | Decision latency, missing inputs, priority changes |
| Dormancy | Extended periods with no activity | Paused or abandoned work |
| Thrashing | Repeated rounds that keep expanding | Scope churn, conflicting feedback |
| Fragmentation | High file-switching and concurrent work | Too many parallel projects, context switching |
| Watcher drag | Many viewers, few builders | Stakeholder review load, unclear ownership |
At portfolio level, FlowStatus highlights the dominant systemic issue rather than every edge case. A portfolio full of stalls points to decision speed and stakeholder alignment; widespread thrashing points to scope stability.
Worked example
Three hypothetical projects of similar size, read through all three signals:
| Project | Focus | Momentum | Friction | Reading |
|---|---|---|---|---|
| Checkout redesign | High: sustained sessions | Strong | Fast, converging | Healthy. Document what made the brief work. |
| Onboarding refresh | Low: constant file-hopping | Moderate | Thrashing, expanding | Scope unstable. Fix alignment before adding people. |
| Maps settings | Moderate | Low | Stalled, with a dormant spell | Blocked. Find the pending decision or close it. |
No single metric tells the story. Onboarding refresh looks busy (reasonable Momentum), but its Focus and Friction signals together show effort that is not converging. That combination is the pattern the benchmark associates with weaker outcomes.
Validation
The 2026 Design Telemetry Benchmark tested these signals against outcomes across 43 projects in six organisations:
- File-switching was the strongest predictor of outcomes among the factors examined (McFadden pseudo-R² 0.15 alone; 0.21 with team size).
- Duration and momentum together explained less (0.11) than switching alone.
- Viewer-heavy teams scored lower (0.11), supporting the watcher-drag signal.
- First-21-day activity, momentum and switching correlated 0.97–0.98 with full-project values, so the signals are usable by week three.
Wave 2, opening October 2026, will test momentum, iteration and friction effects against independent performance data.
Limits and guardrails
- Proxies, not quality. The signals describe working conditions. Pair them with your own judgement of design quality and delivery.
- Systems, not individuals. Use them to understand projects, teams and portfolios, not to rank designers. Low focus usually reflects scope, staffing or stakeholder load.
- Viewer traffic distorts switching. Organisations with heavy view-only activity may show lower switching for reasons unrelated to focus.
- CSV exports lack fine-grained edit events. Views, creates, renames, moves and exports carry the signal, so compare levels within one data source.
- Relative, not absolute. High and low bands are relative to your portfolio (or the benchmark sample), not universal norms.
- Small projects are suppressed. Projects with too little activity are not scored.
Glossary
- Passive telemetry
- Behavioural data emitted automatically by the tools people already use, collected without surveys, plugins, time tracking or screen recording.
- Activity log
- A time-stamped record of actions in a tool. In Figma, the organisation activity log records who did what, to which file or resource, and when.
- Session
- A continuous block of one designer's activity on one project, ending when they step away from it for an extended period.
- Switch rate
- The share of a designer's actions where their very next action is on a different file. Higher means more file-hopping and lower focus.
- Focus
- How well designers can sustain attention on a problem without context switching.
- Momentum
- How consistently a project is worked on across its life, as opposed to stop-start activity.
- Friction
- Observable resistance to progress: stalls, dormancy, rework that does not converge, fragmented load and viewer-heavy participation.
- Work round
- A burst of activity on a project, separated from the next burst by a pause.
- Convergence
- Whether successive work rounds are narrowing towards an outcome or still expanding.
- Thrashing
- Many rounds of rework that are not converging towards an outcome.
- Dormancy
- An extended period with no activity on a project.
- Stalled project
- A project with little iteration and long gaps between the rounds it does have.
Frequently asked questions
What is passive telemetry in design operations?
Passive telemetry is behavioural data generated automatically by the tools design teams already use, such as Figma activity logs. It records who acted, when, what kind of action and on which file, without surveys, plugins, time tracking or screen recording. FlowStatus uses it to measure Focus, Momentum and Friction across teams and projects.
How is design team focus measured from Figma data?
Focus is derived from how designers move between files and how their work breaks into sessions. Sustained work on a small set of files, in fewer and longer sessions, indicates high focus; frequent hopping between files in short bursts indicates fragmented attention. In the 2026 Design Telemetry Benchmark, low file-switching was the strongest predictor of project outcomes among the factors examined.
How is momentum measured for a design project?
Momentum reflects how consistently a project is worked on across its life. Projects with activity on most days score highly; stop-start projects with long pauses score lower, and extended inactivity is flagged as dormancy.
How do you measure friction in design work?
Friction is not a single number. FlowStatus infers it from the shape of activity over time: projects that stall between rounds of work, go dormant, keep reworking without converging, carry fragmented load, or attract many viewers but few builders.
Are Focus, Momentum and Friction measures of design quality?
No. They are proxies for the working conditions under which good design tends to happen. In the 2026 Design Telemetry Benchmark, low file-switching predicted better self-reported business and customer outcomes, but the metrics should be used to spot conditions and investigate, not to grade the quality of design work.
Does FlowStatus read Figma file contents?
No. FlowStatus uses activity metadata only: actor, timestamp, action type and file, project and team names. It does not store designs, prototypes, canvas contents, comment bodies or passwords, and the Figma connection is read-only.
Should these metrics be used to rank individual designers?
No. The signals describe systems, such as projects, teams and portfolios. Low focus usually reflects scope, stakeholder load or staffing decisions rather than individual effort. FlowStatus leadership views are built around organisations, teams, projects and divisions.